Prof. Dr. Rudolf Marcel Füchslin

Projects

• Mira: Hybrid Logic-AI for Claims / Team member / ongoing
• Blockchain-Enabled Financing of Supply Chains / Team member / ongoing
• Data-based Optimization of Outcomes: Successful Technology-Supported Therapy / Co-project leader / ongoing
• Bio-hybrid materials for bioprinting and tumour-targeted therapies (Bio-HhOST in ELM) / Co-project leader / ongoing
• Next Generation 3D Tissue Models: Bio-Hybrid Hierarchical Organoid-Synthetic Tissues (Bio-HhOST) – Comprised of Live and Artificial Cells / Project leader / ongoing
• Stability of self-organizing net fragments as inductive bias for next-generation deep learning / Team member / completed
• Neurological ICU Data / Project leader / completed
• Workshop European Centre for Living Technology / Project leader / completed
• AI powered CBCT for improved Combination Cancer Therapy / Team member / completed
• Automated Release Testing System / Project leader / completed
• Ecological and economic process optimization in cement production through machine learning / Team member / completed
• Extension SARS-CoV-2 Intervention modelling / Project leader / completed
• Creation of advanced cancer treatment planning to boost the effect of Radiotherapy by combining with hyperthermia, heating the tumor / Deputy project leader / completed
• Decision support for pandemics / Project leader / completed
• European Conference Series on Artificial Intelligence in Industry and Finance / Team member / completed
• Machine learning for NMR spectroscopy / Team member / completed
• SARS-CoV2 Modeling of Interventions on the Dynamics of the Pandemics / Project leader / completed
• DIR3CT: Deep Image Reconstruction through X-Ray Projection-based 3D Learning of Computed Tomography Volumes / Team member / completed
• Computational Archaeology / Project leader / completed
• SCIS Simulation Based Calibration of Infusion Systems / Project leader / completed
• Artificial Cells with Distributed Cores to Decipher Protein Function / Project leader / completed
• Data Driven Medical muscle Training / Project leader / completed
• Feasibility Study Reinforcement Learning for Heating Systems / Team member / completed
• 3rd European COST Conference on Mathematics for Industry in Switzerland / Team member / completed
• PhD Network in Data Science / Deputy project leader / completed
• Strategy planning for pandemics in Switzerland / Project leader / completed
• 2nd European COST Conference on Mathematics for Industry in Switzerland / Team member / completed
• Libra: A One-Tool Solution for MLD4 Compliance / Team member / completed
• Complexity 4.0 / Team member / completed
• Thermal Dosimetric Concept for Evaluating Synergistic Effect of Combined Hyperthermia-Radiotherapy / Co-project leader / completed
• Adaptive energy management system for buildings / Team member / completed
• 1st European COST Conference on Mathematics for Industry in Switzerland / Team member / completed
• Model of a Sieving machine (continuation) / Project leader / completed
• Model-based optimisation of combined anti-cancer therapy with heat and radiation / Team member / completed
• Dynamic in vivo profiling of DNA damage and -repair after ionizing radiation / Team member / completed
• SoE Project MPIG / Project leader / completed
• Econimo / Project leader / completed

Publications

Articles in scientific journal, peer-reviewed

• Rainford, P. F. et al. (2026) 'Knowledge preservation in the era of big science and AI : strategies for sustainable scientific research', Nature Communications, 17(4069). doi: 10.1038/s41467-026-72667-3.
• Baulin, V. A. et al. (2026) 'Material‐based intelligence : autonomous adaptation and embodied computation in physical substrates', Advanced Intelligent Systems, 8(5), p. e202501450. doi: 10.1002/aisy.202501450.
• Baulin, V. A. et al. (2025) 'Intelligent soft matter : towards embodied intelligence', Soft Matter, 21(21), pp. 4129–4145. doi: 10.1039/d5sm00174a.
• Bischof, L. et al. (2025) 'Hybrid quantum neural networks show strongly reduced need for free parameters in entity matching', Scientific Reports, 15(1), p. 4318. doi: 10.1038/s41598-025-88177-z.
• Mingo Barba, S. et al. (2024) 'The use of survival dose-rate dependencies as theoretical discrimination criteria for in-silico dynamic radiobiological models', Dose-Response, 22(3). doi: 10.1177/15593258241279906.
• Mingo Barba, S. et al. (2024) 'Theoretical evaluation of the impact of diverse treatment conditions by calculation of the tumor control probability (TCP) of simulated cervical cancer Hyperthermia-Radiotherapy (HT-RT) treatments in-silico', International Journal of Hyperthermia, 41(1), p. 2320852. doi: 10.1080/02656736.2024.2320852.
• Dieper, A. et al. (2024) 'Literature review: potential non-thermal molecular effects of external radiofrequency electromagnetic fields on cancer', International Journal of Hyperthermia, 41(1), p. 2379992. doi: 10.1080/02656736.2024.2379992.
• Fankhauser, T. et al. (2023) 'Multiple query optimization using a gate-based quantum computer', IEEE Access, 11, pp. 114031–114043. doi: 10.1109/ACCESS.2023.3324253.
• Hostettler, M. et al. (2023) 'Modelling of peristaltic pumps with respect to viscoelastic tube material properties and fatigue effects', Fluids, 8(9), pp. 254–269. doi: 10.3390/fluids8090254.
• Amirian, M. et al. (2023) 'Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks', Medical Physics, 50(10), pp. 6228–6242. doi: 10.1002/mp.16405.
• Monteiro Simoes, R. D. et al. (2023) 'Experimental evaluation of quantum machine learning algorithms', IEEE Access, 11, pp. 6197–6208. doi: 10.1109/ACCESS.2023.3236409.
• Schilling, F.-P. et al. (2022) 'Foundations of Data Science : a comprehensive overview formed at the 1st International Symposium on the Science of Data Science', Archives of Data Science, Series A, 8(2). doi: 10.5445/IR/1000146422.
• Füchslin, R. M. and Flumini, D. (2022) 'AI as Arational Intelligence?', Archives of Data Science, Series A, 8(2). doi: 10.5445/IR/1000150236.
• Viecelli, C. et al. (2021) 'Algorithmic extraction of smartphone accelerometer-derived mechano-biological descriptors of resistance exercise is robust to changes in intensity and velocity', PLOS ONE , 16(7), p. e0254164. doi: 10.1371/journal.pone.0254164.
• Viecelli, C. et al. (2020) 'Using smartphone accelerometer data to obtain scientific mechanical-biological descriptors of resistance exercise training', PLOS ONE, 15(7), p. e0235156. doi: 10.1371/journal.pone.0235156.
• Weyland, M. S. et al. (2020) 'Holistic view on cell survival and DNA damage : how model-based data analysis supports exploration of dynamics in biological systems', Computational and Mathematical Methods in Medicine, 2020. doi: 10.1155/2020/5972594.
• Bosch, J., Füchslin, R. M. and Zaugg, C. (2019) 'Multiple regimes in operation of the Swiss railway system and potential influences on power load', IEEE Transactions on Intelligent Transportation Systems, 20(5), pp. 1697–1705. doi: 10.1109/TITS.2018.2833961.
• Schulz, N. et al. (2017) 'Dynamic in vivo profiling of DNA damage and repair after radiotherapy using canine patients as a model', International Journal of Molecular Sciences, 18(6/1176). doi: 10.3390/ijms18061176.
• Baltensperger, T. et al. (2017) 'European Union gas market development', Energy Economics, 66, pp. 466–479. doi: 10.1016/j.eneco.2017.07.002.
• Miyashita, S. et al. (2015) 'Mechanical catalysis on the centimetre scale', Journal of the Royal Society Interface, 12(104). doi: 10.1098/rsif.2014.1271.
• Baltensperger, T. et al. (2015) 'Multiplicity of equilibria in conjectural variations models of natural gas markets', European Journal of Operational Research, 252(2). doi: 10.1016/j.ejor.2016.01.032.
• Fellermann, H. et al. (2014) 'Formalizing modularization and data hiding in synthetic biology', ACM Journal on Emerging Technologies in Computing Systems, 11(3/24). doi: 10.1145/2667231.
• Füchslin, R. M. et al. (2014) 'Morphological control : a design principle for applications in space science', Journal of the British Interplanetary Society, 67, pp. 305–313. Available at: http://adsabs.harvard.edu/abs/2014JBIS...67..305F.
• Füchslin, R. M. et al. (2013) 'Morphological computation and morphological control : steps toward a formal theory and applications', Artificial Life, 19(1), pp. 9–34. doi: 10.1162/ARTL_a_00079.
• Hauser, H. et al. (2013) 'Introduction to the special issue on morphological computation', Artificial Life, 19(1), pp. 1–8. doi: 10.1162/ARTL_e_00083.
• Weyland, M. S. et al. (2013) 'The MATCHIT automaton : exploiting compartmentalization for the synthesis of branched polymers', Computational and Mathematical Methods in Medicine, 2013(467428). doi: 10.1155/2013/467428.
• Scheidegger, S. et al. (2013) 'Using state variables to model the response of tumour cells to radiation and heat : a novel multi-hit-repair approach', Computational and Mathematical Methods in Medicine, 2013(587543). doi: 10.1155/2013/587543.
• Hauser, H. et al. (2012) 'The role of feedback in morphological computation with compliant bodies', Biological Cybernetics, 106(10), pp. 595–613. doi: 10.1007/s00422-012-0516-4.
• Filisetti, A. et al. (2012) 'A stochastic model of autocatalytic reaction networks', Theory in Biosciences, 131(2), pp. 85–93. doi: 10.1007/s12064-011-0136-x.
• Nakajima, K. et al. (2012) 'Morphology-induced collective behaviors : dynamic pattern formation in water-floating elements', PLOS ONE, 7(6/e37805). doi: 10.1371/journal.pone.0037805.
• Filisetti, A. et al. (2011) 'A stochastic model of the emergence of autocatalytic cycles', Journal of Systems Chemistry, 2(2). doi: 10.1186/1759-2208-2-2.
• Hauser, H. et al. (2011) 'Towards a theoretical foundation for morphological computation with compliant bodies', Biological Cybernetics, 105(5-6), pp. 355–370. doi: 10.1007/s00422-012-0471-0.

Books, peer-reviewed

• Hauser, H., Füchslin, R. M. and Pfeifer, R. (eds) (2014) Opinions and outlooks on morphological computation. Zürich: Universität Zürich. doi: 10.21256/zhaw-3157.
• Serra, R. et al. (eds) (2013) Complex systems models in biology and medicine : generic properties and applications. London: Hindawi. doi: 10.1155/2014/580509.

Book chapters, peer-reviewed

• Hollenstein, L. et al. (2019) 'Unsupervised learning and simulation for complexity management in business operations', in Braschler, M., Stadelmann, T., and Stockinger, K. (eds) Applied data science : lessons learned for the data-driven business. Cham: Springer, pp. 313–331. doi: 10.1007/978-3-030-11821-1_17.
• Miyashita, S. et al. (2011) 'Basic problems in self-assembling robots and a case study of segregation on tribolon platform', in Meng, Y. and Yaochu, J. (eds) Bio-inspired self-organizing robotic systems. Berlin: Springer, pp. 173–191. doi: 10.1007/978-3-642-20760-0_8.

Written conference contributions, peer-reviewed

• Peterko, Y. et al. (2025) '"So, why did you do that?" : exploring therapists" reasoning and decision-making in the use of technology for neurorehabilitation: a preliminary analysis', in MiNT UK 2025 'Neurotechnology in Practice: Measuring Impact on Patient Outcomes', London, United Kingdom, 16 October 2025. Winterthur: ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-34707.
• Schmid, N. et al. (2025) 'MolDETR : next-generation analysis of molecular spectra with deep learning', in 21st European Magnetic Resonance Congress (EUROMAR), Oulu, Finnland, 6-10 July 2025. Oulu: EUROMAR. doi: 10.21256/zhaw-33659.
• Zaugg, C. et al. (2024) 'How to turn a leaky learner into a sealed one', in Villano, M., Cagnoni, S., and Serra, R. (eds) Artificial Life and Evolutionary Computation. Cham: Springer, pp. 29–40. doi: 10.1007/978-3-031-57430-6_3.
• Bolt, P. et al. (2024) 'A simulation study on energy optimization in building control with reinforcement learning', in Suen, C. Y. et al. (eds) Artificial Neural Networks in Pattern Recognition. Cham: Springer. doi: 10.1007/978-3-031-71602-7_27.
• Mingo Barba, S. et al. (2023) 'Tumor Control Probability (TCP) study to theoretically assess the impact of different clinical conditions in Hyperthermia plus Radiotherapy (HT+RT) treatments', in 35th Annual Meeting European Society for Hyperthermic Oncology, Cologne, Germany, 26-29 September 2023.
• Scheidegger, S., Füchslin, R. M. and Gaipl, U. S. (2023) 'Multi – vs. single – perceptron approach for modelling the pattern recognition and classification in a multi-compartment adaptive immune system model', in ALIFE 2023: Ghost in the Machine : Proceedings of the 2023 Artificial Life Conference. Cambridge: MIT Press, p. 7. doi: 10.1162/isal_a_00574.
• Weyland, M. S. et al. (2023) 'A chemical compiler for the synthesis of branched oligomers on standardized chemical reaction structures', in ALIFE 2023: Ghost in the Machine : Proceedings of the 2023 Artificial Life Conference. Cambridge: MIT Press, p. 105. doi: 10.1162/isal_a_00648.
• Schneider, J. J. et al. (2023) 'Artificial chemistry performed in an agglomeration of droplets with restricted molecule transfer', in De Stefano, C., Fontanella, F., and Vanneschi, L. (eds) Artificial Life and Evolutionary Computation. Cham: Springer, pp. 107–118. doi: 10.1007/978-3-031-31183-3_9.
• Matuttis, H.-G. et al. (2023) 'Computational investigation of the clustering of droplets in widening pipe geometries', in De Stefano, C., Fontanella, F., and Vanneschi, L. (eds) Artificial Life and Evolutionary Computation. Cham: Springer, pp. 82–93. doi: 10.1007/978-3-031-31183-3_7.
• Schneider, J. J. et al. (2023) 'Network creation during agglomeration processes of polydisperse and monodisperse systems of droplets', in De Stefano, C., Fontanella, F., and Vanneschi, L. (eds) Artificial Life and Evolutionary Computation. Cham: Springer, pp. 94–106. doi: 10.1007/978-3-031-31183-3_8.
• Matuttis, H.-G. et al. (2023) 'The good, the bad and the ugly : droplet recognition by a "shootout"-heuristics', in Artificial Life and Evolutionary Computation. Cham: Springer, pp. 51–62. doi: 10.1007/978-3-031-23929-8_5.
• Schneider, J. J. et al. (2023) 'Obstacles on the pathway towards chemical programmability using agglomerations of droplets', in Artificial Life and Evolutionary Computation. Cham: Springer. doi: 10.1007/978-3-031-23929-8_4.
• Füchslin, R. M. et al. (2023) 'Ethical aspects of computational modelling in science, decision support and communication', in Artificial Life and Evolutionary Computation. Cham: Springer. doi: 10.1007/978-3-031-23929-8_24.
• Schneider, J. J. et al. (2023) 'Geometric restrictions to the agglomeration of spherical particles', in Artificial Life and Evolutionary Computation. Cham: Springer. doi: 10.1007/978-3-031-23929-8_7.
• Schneider, J. J. et al. (2023) 'Investigation of the Ramsey-Pierce-Bowman model', in Artificial Life and Evolutionary Computation. Cham: Springer. doi: 10.1007/978-3-031-23929-8_23.
• Schneider, J. J. et al. (2023) 'Exploring the three-dimensional arrangement of droplets', in Artificial Life and Evolutionary Computation. Cham: Springer. doi: 10.1007/978-3-031-23929-8_6.
• Schneider, J. J. et al. (eds) (2023) Artificial Life and Evolutionary Computation : 15th Italian Workshop, WIVACE 2021, Winterthur, Switzerland, September 15–17, 2021, XV International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Winterthur, Switzerland, 15-17 September 2021. Cham: Springer. doi: 10.1007/978-3-031-23929-8.
• Hotz, P. E. et al. (2022) 'Simulations of vesicular disentanglement', in Holler, S., Löffler, R., and Bartlett, S. (eds) ALIFE 2022: The 2022 Conference on Artificial Life. Cambridge: MIT Press, p. 25. doi: 10.1162/isal_a_00505.
• Mingo Barba, S. et al. (2022) 'Repair protein damage vs. cell repair saturation : a comparison of its use in radiobiological models', in 26th Annual SASRO Meeting, Baden, Switzerland, 1-3 September 2022.
• Herzig, I. et al. (2022) 'Deep learning-based simultaneous multi-phase deformable image registration of sparse 4D-CBCT', in Medical Physics. American Association of Physicists in Medicine, pp. e325–e326. doi: 10.1002/mp.15769.
• Schneider, J. J. et al. (2021) 'Influence of the geometry on the agglomeration of a polydisperse binary system of spherical particles', in ALIFE 2021: The 2021 Conference on Artificial Life. Cambridge: MIT Press, p. 71. doi: 10.1162/isal_a_00392.
• Chehda Moreno, N. et al. (2021) 'Interpreting difference measures for social contact matrices : impact on the pandemic dynamics', in 8th International Conference on Infectious Disease Dynamics (Epidemics8), online, 30 November - 3 December 2021.
• Flumini, D. et al. (2020) 'Towards programmable chemistries', in Cicirelli, F. et al. (eds) Artificial Life and Evolutionary Computation. Springer. doi: 10.1007/978-3-030-45016-8_15.
• Schneider, J. J. et al. (2020) 'Studying and simulating the three-dimensional arrangement of droplets', in Cicirelli, F. et al. (eds) Artificial Life and Evolutionary Computation. Cham: Springer. doi: 10.1007/978-3-030-45016-8_16.
• Gygax, G., Füchslin, R. M. and Ott, T. (2020) 'Self-organized division of labor in networks of forecasting models for time series with regime switches', in Proceedings of the NOLTA 2020 Conference, pp. 278–281.
• Schneider, J. J. et al. (2020) 'Investigating three-dimensional arrangements of droplets', in Cicirelli, F. et al. (eds) Artificial Life and Evolutionary Computation. Cham: Springer, pp. 171–184. doi: 10.1007/978-3-030-45016-8_17.
• Weyland, M. et al. (2019) 'Dynamic DNA damage and repair modelling : bridging the gap between experimental damage readout and model structure', in Cagnoni, S. et al. (eds) Artificial Life and Evolutionary Computation. Cham: Springer, pp. 127–137. doi: 10.1007/978-3-030-21733-4_10.
• Schneider, J. J. et al. (2019) 'Simulation of a microfluidic system of droplets', in Joint Annual Meeting of the Swiss Physical Society and the Austrian Physical Society, Zurich, 26-30 August 2019.
• Fellermann, H. et al. (eds) (2019) Alife 2019 : proceedings of the Artificial Life Conference 2019, The 2019 Conference on Artificial Life, Newcastle, United Kingdom, 29 July - 2 August 2019. Massachusetts Institute of Technology. doi: 10.1162/isal_a_00240.
• Fellermann, H. et al. (2019) 'Artificial life in a challenged world', in Proceedings of the Artificial Life Conference 2019. Massachusetts Institute of Technology. doi: 10.1162/isal_a_00123.
• Fellermann, H. et al. (2019) 'Towards low-carbon conferencing : acceptance of virtual conferencing solutions and other sustainability measures in the ALIFE community', in Fellermann, H. et al. (eds) Proceedings of the Artificial Life Conference 2019. Massachusetts Institute of Technology, pp. 21–27. doi: 10.1162/isal_a_00133.
• Füchslin, R. M. et al. (2019) 'Simplified modeling of the evolution of skills in a spatially resolved environment', in Fellermann, H. et al. (eds) Proceedings of the Artificial Life Conference 2019. Massachusetts Institute of Technology, pp. 324–330. doi: 10.1162/isal_a_00182.
• Bolt, P. et al. (2018) 'Model predictive control for building automation', in EuroSun 2018 : conference proceedings. International Solar Energy Society, pp. 1330–1341. doi: 10.18086/eurosun2018.11.05.
• Scheidegger, S. et al. (2015) 'A novel approach for thermal dosimetry', in Proceedings of the ESHO Annual Meeting 2015. Zürich: ESHO, p. 26.
• Chaachouay, H. et al. (2015) 'Monitoring of DNA damage and repair kinetics during radiotherapy in vivo : a minimally invasive approach using the dog as a model', in Molecular radiation biology/oncology : proceedings of 14th international wolfsbergmeeting, p. 22.
• Jaeger, C. et al. (2014) 'Performance prediction and optimization for industrial sieves by simulation : a two-tier approach', in Deatcu, C. and Wittman, J. (eds) ASIM 2014: 22. Symposium Simulationstechnik: 3. bis 5. September 2014: HTW Berlin: 2, Tagungsband: Teil II. Wien: Argesim, pp. 299–306. doi: 10.21256/zhaw-1653.
• Scheidegger, S., Fuchs, H. U. and Füchslin, R. M. (2014) 'Computational methods for exploring the dynamics of cancer : the potential of state variables for description of complex biological systems', in Proceedings of the international symposium on nonlinear theory and its applications : NOLTA2014, Luzern, Switzerland, september 14-18, 2014. NOLTA Society, pp. 168–171. doi: 10.21256/zhaw-1764.
• Scheidegger, S., Grosse, N. and Füchslin, R. M. (2014) 'Homologous recombination in the view of the MHR-model', in Klöck, S. (ed.) Joint conference of the SSRMP, DGMP, ÖGMP : Dreiländertagung der Medizinischen Physik - Abstractbook. Zürich: SGSMP/DGMP/ÖGMP, pp. 194–195.
• Bernhardsgrütter, R. et al. (2014) 'Employing L-systems to generate mass-spring networks for morphological computing', in Proceedings of the 2014 International Symposium on Nonlinear Theory and its Applications (NOLTA2014). Luzern: IEICE, pp. 168–171. doi: 10.21256/zhaw-1660.
• Scheidegger, S. et al. (2013) 'Characterization of hyperthermia with radiotherapy : temporal homogeneity and limitations of the CEM concept', in Proceedings of the 28th annual meeting of the european society for hyperthermic oncology 2013, p. 131.
• Scheidegger, S. et al. (2012) 'Dynamic modelling of the synergistic effect of hyperthermia and radiotherapy', in Radiotherapy & Oncology. Elsevier, p. s356. doi: 10.1016/S0167-8140(12)71237-9.
• Buecheler, T. et al. (2011) 'Modeling and simulating crowdsourcing as a complex biological system : human crowds manifesting collective intelligence on the internet', in Lenaerts, T. et al. (eds) Advances in artificial life, ECAL 2011 : proceedings of the eleventh European conference on the synthesis and simulation of living systems. Cambridge: MIT Press, pp. 109–116. doi: 10.21256/zhaw-1672.
• Füchslin, R. M. et al. (2011) 'Morphological computation : applications on different scales exploiting classical and statistical mechanics', in Proceedings of the 2nd international conference on morphological computation, pp. 41–44.
• Scheidegger, S. and Füchslin, R. M. (2011) 'Kinetic model for dose equivalent : an efficient way to predict systems response of irradiated cells', in Bödi, R. and Maurer, W. (eds) Proceedings of ASIM 2011 : Grundlagen, Methoden und Anwendungen in Modellbildung und Simulation. Arbeitsgemeinschaft Simulation. doi: 10.21256/zhaw-3558.
• Tientcheu Ngouabeu, A. M. et al. (2010) 'Self-organized segregation effect on self-assembling robots', in Fellermann, H. et al. (eds) Artificial live XII : proceedings of the twelfth international conference on the synthesis and simulation of living systems. Cambridge: MIT Press, pp. 232–238. doi: 10.21256/zhaw-4112.
• Füchslin, R. M. et al. (2010) 'Dynamical stability of autocatalytic sets', in Fellermann, H. et al. (eds) Artificial live XII : proceedings of the twelfth international conference on the synthesis and simulation of living systems. Cambridge: MIT Press, pp. 65–72. doi: 10.21256/zhaw-4097.
• Bücheler, T. et al. (2010) 'Crowdsourcing, open innovation and collective intelligence in the scientific method : a research agenda and operational framework', in Fellermann, H. et al. (eds) Artificial live XII : proceedings of the twelfth international conference on the synthesis and simulation of living systels. Cambridge: MIT Press, pp. 679–686. doi: 10.21256/zhaw-4094.

Other publications

• Füchslin, R. et al. (2025) 'Life at the edge of chaos', ANG Fokus, 2025, pp. 36–41. Available at: https://ang.ch/de/publikationen/uuid/i/ad4024db-d71e-5ad1-aa29-258d2f991872-ANG_Fokus_2025.
• Füchslin, R., Flumini, D. and Weyland, M. (2025) 'Chaos 2.0 – Formen der Unvorhersehbarkeit', ANG Fokus, 2025, pp. 41–47. Available at: https://ang.ch/de/publikationen/uuid/i/ad4024db-d71e-5ad1-aa29-258d2f991872-ANG_Fokus_2025.
• Peterko, Y. et al. (2025) 'User-centered design (UCD) of a clinical decision support system (CDSS) in neurorehabilitation : a study protocol', in Summer School 'Towards a Continuum of Technology-assisted Therapy (TCTT)', Brissago, Switzerland, 23-27 June 2025. Winterthur: ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-34708.
• Füchslin, R. M. (2024) 'Seltene und elegante Formeln', ANG Fokus, 2024, pp. 34–39. Available at: https://ang.ch/de/publikationen/uuid/i/18898fe8-3ba1-5f9a-9f9a-578f455c2e75-ANG_Fokus_2024.
• Henrici, A. et al. (eds) (2023) Artificial Intelligence in Finance and Industry : Volume II - Highlights from the 7th European Conference, 7th European COST Conference on Artificial Intelligence in Industry and Finance, Winterthur, Switzerland, 28 September 2022. Frontiers Research Foundation. Available at: https://www.frontiersin.org/research-topics/38909/.
• Henrici, A., Füchslin, R. M. and Schwendner, P. (2023) 'Editorial: Artificial Intelligence in Finance and Industry: volume II—highlights from the 7th European conference', Frontiers in Artificial Intelligence, 6(1267377). doi: 10.3389/frai.2023.1267377.
• Bolt, P. et al. (2023) 'Optimizing cement production by employing physics informed machine learning', in Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. doi: 10.21256/zhaw-26666.
• Deflorin, P. et al. (eds) (2022) Artificial Intelligence in Finance and Industry : highlights from 6 European COST conferences, 5th European COST Conference on Artificial Intelligence in Industry and Finance, Winterthur, Switzerland (online), 3 September 2020. Frontiers Research Foundation. Available at: https://www.frontiersin.org/research-topics/18514/.
• Schneider, J. J. et al. (2022) 'Paths in a network of polydisperse spherical droplets', in ALIFE 2022: The 2022 Conference on Artificial Life. Cambridge: MIT Press, p. 23. doi: 10.1162/isal_a_00502.
• Füchslin, R. M. et al. (2022) 'Minimal models for spatially resolved population dynamics : applications to coexistence in multi – trait models', in ALIFE 2022: The 2022 Conference on Artificial Life. Cambridge: MIT Press, p. 75. doi: 10.1162/isal_a_00504.
• Füchslin, R. M. (2021) Cross Roads #21: Morphological Computation and Control. Cross Labs / Cross Compass. Available at: https://www.youtube.com/watch?v=BTgCp5iIllc&t=364s.
• Weyland, M. S. et al. (2020) 'A compiler framework to derive microfluidic platforms for manufacturing hierarchical, compartmentalized structures that maximize yield of chemical reactions', in ALIFE 2020: The 2020 Conference on Artificial Life. Cambridge: MIT Press, pp. 602–604. doi: 10.1162/isal_a_00303.
• Füchslin, R. M. (2020) 'AI = Arational Intelligence?', ANG-Fokus, 2020(1), pp. 26–29.
• Füchslin, R. M. (2020) Künstliche Intelligenz. Aargauische Naturforschende Gesellschaft. Available at: https://anchor.fm/ang1811/episodes/3---Knstliche-Intelligenz-eapt21.
• Krütli, P. et al. (2018) Prioritätenliste und Kontingentberechnung : Pandemievorbereitung in der Schweiz. 2. Auflage. Zürich: ETH Zürich. doi: 10.21256/zhaw-5543.
• Krütli, P. et al. (2017) Liste des priorités et calcul des contingents : préparation aux pandémies en Suisse. 2. Auflage. Zürich: ETH Zürich. doi: 10.21256/zhaw-5544.
• Füchslin, R. M. (2016) Theory in the applied sciences, Invited talk Norbert Straumann to his 80th birthday, Seminar in Lavin, organized by Prof. Ruedi Stoop.
• Scheidegger, S. and Füchslin, R. M. (2014) 'In vitro, in vivo, in silico : Modellbildung und Computersimulation als komplementäre Labormethode', ANG Fokus, 1, pp. 82–97.
• Füchslin, R. M. (2014) Morphological control as guiding principle in physiology and medical applications, Invited talk ShanghAI Lectures of Prof. Rolf Pfeifer.
• Füchslin, R. M. (2013) 'Morphological Control', Aktuelle Technik, 2013(8), pp. 34–35. doi: 10.21256/zhaw-1665.
• Füchslin, R. M. (2012) 'Wozu brauchen wir Curiosity?', Journal 21.

Oral conference contributions and abstracts

• Füchslin, R. M. (2026) 'Applying applied science : being a ferryman between the ivory tower, R&D departments and decision making in the age of artificial intelligence', in KAAC, Seoul, South Korea, 22 June 2026.
• Füchslin, R. M. (2025) 'The Zurich University of Applied Sciences ZHAW School of Engineering', in Open Day for Students of Engineering, Univ. Ca'Forscari, Venice, Italy, 18 December 2025.
• Füchslin, R. M. et al. (2025) 'AI : more a method than magic', in RehabWeek, Chicago, USA, 10.-17. May, 2025.
• Füchslin, R. M. and Weyland, M. (2024) 'Application-oriented modelling in science, technology and decision support : lessons from knowledge transfer across the boundaries of science', in G2W: Genomics to Whole Cell Workshop, Sheffield, United Kingdom, 23-25. October 2024.
• Füchslin, R. M. (2024) 'Morphological process control : morphological computing brings a novel perspective into the life sciences', in MorphoTalks season 2, Bristol, United Kingdom, 20. March, 2024.
• Füchslin, R. M. (2024) 'Ethical aspects of computational modelling', in Workshop Model‐based data analysis for clinical applications, Winterthur, Switzerland, 14. February 2024.
• Füchslin, R. M. (2024) 'Quantum computing in a nutshell', in Tagung der Gesellschaft für Mathematik an Schweizer Hochschulen (GMFH), 20. Januar 2024.
• Füchslin, R. M. (2024) 'Multi-scale models in life sciences and epidemiology', in Workshop Model‐based data analysis for clinical applications, Winterthur, Switzerland, 8.-10. January 2026.
• Füchslin, R. M. (2023) 'Decision support vs. wheather forecasting : ethical and social aspects of computational modelling in science, decision support and communication', in ZHAW School of Health Sciences, Seminar, Winterthur, Switzerland, 13 September 2023.
• Füchslin, R. M. (2023) 'Applying artificial chemistry : the Kauffman Model justifies novel technologies', in WIVACE - XVII International Workshop on Artificial Life and Evolutionary Computation, Venice, Italy, 6.-8. September 2023.
• Schneider, J. J. et al. (2023) 'Bidisperse extension of the kissing number problem', in 28th International Conference on Statistical Physics (Statphys28), Tokyo, Japan, 7-11 August 2023.
• Füchslin, R. M. (2023) 'Gate-based Quantum Computing und Quantum Annealing : zwei Wege zu Quantenanwendungen', in Innovation Kick - Quantum Computing, Winterthur, Switzerland, 4. April 2023. Available at: https://tpw.ch/wp-content/uploads/2023/04/QI_Technopark_v4.pdf.
• Füchslin, R. M. (2022) 'Applied science : the curse and blessing of applying science', in Talk at Newcastle University, Newcastle, United Kingdom, 15 March 2022.
• Mingo Barba, S. et al. (2022) 'The use of qualitative and quantitative hyperthermic effects as discrimination criteria in radiobiological models', in 34th Annual Meeting European Society for Hyperthermic Oncology, Gothenburg, Sweden, 14-17 September 2022.
• Mingo Barba, S. et al. (2022) 'The use of dose rate dependencies as a theoretical discrimination criteria in radiobiological models', in 4th European Congress of Medical Physics, Dublin, Ireland, 17-20 August 2022.
• Hostettler, M. et al. (2022) 'Modelling of peristaltic pumps for viscoelastic tube material properties under consideration of fatigue effects', in Multiphysics 2022. International Society of Multiphysics, p. 33. Available at: https://static1.squarespace.com/static/5c9f89c101232c1d41297d67/t/639912525a90a93394aa8b71/1670976084271/MULTIPHYSICS+2022-Abstract+Booklet.pdf.
• Füchslin, R. M. (2022) 'Applied complex systems sciences ACSS', in ZHAW Center for Artificial Intelligence, Seminar, Winterthur, Switzerland, 7 December 2022.
• Fankhauser, T. et al. (2021) 'Implementing database and machine learning algorithms on publicly available quantum computers', in Talk at Zurich University, Zurich, Switzerland, 4 May 2021.
• Schneider, J. J. et al. (2021) 'Influence of the geometry on the agglomeration of a polydisperse binary system of spherical particles', in International Conference on Artificial Life (ALIFE), online, 19-23 July 2021. Available at: https://www.youtube.com/watch?v=2uSgimAHU4I.
• Füchslin, R. M. (2021) 'Modeling social systems at ZHAW', in XV International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Winterthur, Switzerland, 15-17 September 2021.
• Füchslin, R. M. (2021) 'Computational approaches in biology', in ACDC Summer School, online, 26-27 August 2021.
• Weber, R. et al. (2020) 'Quantum databases and quantum machine learning : how far can we go on a publicly available quantum computer?', in Datalab Seminar ZHAW, Winterthur, 9. September 2020. Available at: https://www.zhaw.ch/de/forschung/departementsuebergreifende-kooperationen/datalab/datalab-seminar/.
• Füchslin, R. M. et al. (2019) 'Morphological computation and control in medicine and related sciences', in BioDynaMo, Zurich, 2-3 December 2019.
• Schneider, J. J. et al. (2019) 'Exploring the three-dimensional arrangement of droplets', in XIV International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Rende, Italy, 18-20 September 2019.
• Schneider, J. J. and Füchslin, R. M. (2019) 'Simulations of artificial populations with competing skills', in Joint Annual Meeting of the Swiss Physical Society and of the Austrian Physical Society, Zurich, 26-30 August 2019.
• Füchslin, R. M., Schneider, J. J. and Walker, R. (2019) 'Simplified modeling of the evolution of skills in a spatially resolved environment', in The 2019 Conference on Artificial Life, Newcastle, United Kingdom, 29 July - 2 August 2019.
• Fellermann, H. et al. (2019) '2019 Preface', in Proceedings of the Artificial Life Conference 2019. Massachusetts Institute of Technology. doi: 10.1162/isal_e_00239.
• Weyland, M. et al. (2018) 'Dynamic DNA damage and repair modeling : bridging the gap between experimental damage readout and model structure', in XIII International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Parma, Italy, 10-12 September 2018.
• Füchslin, R. M. (2018) 'The role of models in applied sciences', in Talk at SWISSNEX Meeting, Winterthur, 12. Dezember 2018.
• Füchslin, R. M. (2017) 'BionTec 2.0', in Vortrag am TecDay an der Alten Kantonsschule Aarau, Aarau, 9. November 2017.
• Füchslin, R. M. (2017) 'Applied complex systems sciences : the role of models', in Invited Talk at Swiss Banking Advisory Event, 29. September 2017.
• Füchslin, R. M. (2017) 'Applied complex systems sciences', in WIVACE 2017 book of abstracts. Reggio Emilia: Università degli Studi di Modena e Reggio nell'Emilia. Available at: https://wivace.org/2017/files/bookOfAbstracts.pdf.
• Ott, T. and Füchslin, R. M. (2017) 'The future's back : first generic models of self-defeating road traffic forecasting', in NDES 2017, 25th Nonlinear Dynamics of Electronic Systems Conference, Zernez, 5-7 June 2017.
• Füchslin, R. M. (2017) 'Evolution als Werkzeug', in Rotary Club Lenzburg, Lenzburg, 13. März 2017.
• Füchslin, R. M. (2015) 'Morphological control applied embodied intelligence in mechanical and biological systems offering new perspectives to creativity support systems', in Proceedings The Tenth International Conference on Knowledge Information and Creativity Support Systems (KICSS 2015). Thammasat University.
• Füchslin, R. M. (2015) 'Morphological control : applied embodied intelligence in medicine, robotics and IT', in Vortrag ML - Meetup ETH, Zürich, 4. August 2015.
• Füchslin, R. M. (2014) 'Morphological computation and control : von der Robotik zur Funktion der Zelle', in Vortrag Aargauische Naturforschende Gesellschaft, Aarau, 10. Dezember 2014.
• Füchslin, R. M. (2014) 'Morphological computation and control : von der Robotik zur Funktion der Zelle', in Vortrag: Naturwissenschaftliche Gesellschaft Winterthur, Winterthur, 21. Februar 2014.
• Füchslin, R. M. et al. (2013) 'Morphological control as guiding principle in physiology and medical applications', in Int. Workshop on Soft Robotics and Morphological Computation, Ascona, 19 July 2013.
• Hadorn, M. et al. (2012) 'A minimal artificial subcellular matrix', in 13th International Conference on the Simulation & Synthesis of Living Systems (Artificial Life 13), Michigan, USA, 19-22 July 2012.
• Scheidegger, S. et al. (2012) 'The dynamic view to hyperthermia : a comparison of the CEM43° concept', in Strahlentherapie und Onkologie. Springer, p. 738. doi: 10.1007/s00066-012-0181-5.
• Füchslin, R. M. (2012) 'Morphological computation and control : from robotics to implications on anticancer treatment', in Research Colloquium 2012, Aarau, 8. November 2012.
• Füchslin, R. M. (2011) 'Morphological control : applications on different scales exploiting classical and statistical mechanic', in ICMC2011: 2nd International Conference on Morphological Computation, Venice, Italy, 12–14 September 2011.
• Füchslin, R. M. (2010) 'Controlling dynamical architecture contributions from morphological computation and control', in Satellite Workshop of ALIFE XII, Odense, Denmark, 19 August 2010.

Research data

• Eggenberger Hotz, Peter; Luchsinger, Rolf H.; Weyland, Mathias; Jamieson, W. David; Castell, Oliver; Füchslin, Rudolf M., 2026. Code for: Emergent predictability from parameter ambiguity in biochemical networks. Zenodo. Available from: https://doi.org/10.5281/zenodo.19485525
• Enayati, Aref; Baird, Hannah; Weyland, Mathias; Fink, Alke; Lattuada, Marco, Alke; Jamieson, William; Füchslin, Rudolf M.; Castell, Oliver, . Enhanced quantitative accuracy in single molecule imaging : a fidelity-guided denoising approach. Zenodo. Available from: https://doi.org/10.5281/zenodo.19498257

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